Episoder
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01:26 Journey to Snowflake
02:32 Snowflake and AI
06:43 Choosing your model
07:44 Snowflake & OS
09:43 Innovations to reduce training data size
10:59 From large to small models
13:14 Snowflake and agentic systems
15:50 AI & data security
17:17 Access control layer
18:14 Embedded applications
19:55 Data sharing
21:37 Snowflake training & inference
23:12 Data reshaping
24:40 Structured versus unstructured model inputs
25:24 Models providing the mean v. exceptions
27:19 Vector databases
30:33 Summary
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01:43 Tabular Acquisition by Databricks
05:57 BI's Third Form
09:12 Future of BI
12:50 Data Quality in the World of LLMs
18:48 Building Resilient Data Pipelines & ETL
21:01 Evolving Role of BI Analysts
23:18 Data and Decision-Making
28:05 Conclusion
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Mangler du episoder?
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01:55 Big Data is Dead
06:41 Ease of Use
08:54 Hybrid Architecture
10:30 Audience Question: LLMs for Onboarding?
12:55 Hybrid Architecture Enables New Software Design
16:58 DuckDB & ETL
19:24 Duck Puns
22:07 Duck Community
24:32 Summary
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0:00 Office Hours - Evan Cheng
01:28 From Meta to Mysten
04:54 Why Develop a New Language, Move
11:15 Developer Response to Move
13:21 Zero Knowledge (ZK) Proof of Login
19:00 Kiosk
24:34 On Chain Storage Limitations
29:01 DAGs & Web3
30:01 Mysten Labs Ecosystem & SUI
34:03 SUI Token Launch
38:30 Closing
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Takeaways from this discussion include:
There is a pendulum between governance and self-serve, and that swing is narrowing with developments like OmniThere's a dynamic with centralization and decentralization hybrid execution at the edge which allows super-interactive user experiences. As these experiences improve, the number of people who benefit and can access data in meaningful ways only increases.00:06 Introduction
01:27 Being Chief Analytics Officer
04:08 Evolution of BI
08:23 Data Organization Structure
10:53 Data Permissioning Philosophy
14:12 Hybrid Execution
17:36 BI Application Architecture
19:36 Mitigating Buyer Fatigue
21:20 BI & AI
25:59 Semantic Layer
27:12 Audience Question: Should AI Suggest Analyses?
28:43 Embedded Analytics
32:48 Will AI Automate BI Users Away?
35:00 Summary
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00:06 Introduction
02:10 Arbitrum Statistics
02:47 Building Your Developer Community
09:08 Arbitrum One v. Arbitrum Nova
14:55 L3 & Customization
19:41 Arbitrum Orbit & Chain Clusters
24:39 Future Customizations for Developers
28:30 Accepting Developer Languages: To reduce barriers to entry
30:11 Accepting Developer Languages: To access legacy code
32:38 Accepting Developer Languages: To reduce fees
33:48 Convergence of Web2 and Web3
37:55 Community-Source-Software
42:03 Summary
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0:00 Office Hours with Philip Zelitchenko
01:47 Q: How did you decide to structure your team like software engg?
05:07 Q: Determining the value of data 09:17 Structuring data teams: data PMs
10:47 Q: Same data team responsible for internal v. external PRDs?
11:14 Structuring data teams: data engineering 12:02 Q: What is a data product?
12:47 Structuring data teams: data analysts 13:22 Structuring data teams: data governance
13:37 Structuring data teams: data platform
14:18 Q: What distinguishes a DPRD from a PRD?
17:33 Q: Role of the DPRD?
20:05 Q: DPRD v. TEP?
20:55 Demystifying data governance
23:22 Data alert management - internal team and customers
26:20 Q: Motivating ownership of data assets?
28:51 Defining value of a data asset
30:29 Measuring data usage
31:37 Q: Can tools today handle the stochastic nature of data?
33:28 Building a data team within the enterprise
35:42 Q: How to test data products prior to release?
40:00 Q: How do you use observability to manage diversity of alerts?
41:51 Summary
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00:11 Introduction
02:54 What is Outbound Fury (OBF)?
03:34 Inspiration for OBF
05:03 OBF Tactics
07:44 Determining the Line
11:22 The Challenger Sale
14:11 Personas & OBF
16:05 Product-Led Growth (PLG), ABM & Outbound Fury
19:35 Setting Up Your Team for Success
21:54 Managing Internal Stakeholders
25:28 Measuring Success
27:16 Brand & OBF Campaigns
29:25 Pricing in Marketing Considerations
31:47 Analyst Community (e.g. Gartner) & OBF
33:43 Company Scale & OBF
36:23 Conclusions
Materials Mentioned in Today's Session:
-- Raj Sarkar's Post: https://rajsarkar.substack.com/p/mark...
-- Marc Benioff, Behind the Cloud https://www.amazon.com/Behind-Cloud-S...
-- Matthew Dixon, The Challenger Sale https://www.amazon.com/The-Challenger...
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00:00 Introduction to Tom and Oliver
03:07 Overview of PLG at Dropbox
05:30 Overview of PLG at Asana
06:07 How to succeed in PLG end user acquisition phase
09:15 Tactics for Generating Awareness
10:17 Customer Expansion Phase
13:15 When Tension Arises Between PLG & Enterprise Security Needs
15:24 Security is an All Consuming Roadmap, not a Feature
18:35 How the Organization Shifts during the Transition from PLG to SLG
20:48 How Pricing Changes from PLG to SLG
26:22 The PLG Trap
28:03 Avoiding the PLG Trap
31:55 Value-Based Selling: Generalizable or Vertical/Use-Case Specific?
35:35 Atlassian v. Asana's Approaches
37:11 Advice for New Startups Pursuing PLG
38:22 Navigating from SLG to PLG
42:19 Resources for Founders
43:06 PLG, SLG & AI
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On November 29th at 9am Pacific Time, Office Hours hosted Fredrik Haga, founder & CEO of Dune.
Dune is the authoritative source of web3 data. For information on Decentralized Exchange activity, lending volumes, or even the current FTX account balances. I used Dune to make the State of Web3 Presentation.
During this Office Hours, Fredrik & I will talked about
- the importance of data in a decentralized world
- the impact of the three major collapses this year: FTX, Luna, & ThreeArrows on the ecosystem
- the evolution of web3 in 2022
- building a startup through tough market conditions
Thanks to Fredrik for the great session. -
On October 18th at 10am Pacific, Office Hours will host Carilu Dietrich. Carilu headed corporate marketing for Atlassian from $150m to $450m in revenue & through their massively successful IPO.
Since then, she’s advised Segment, Kong, Miro, Bill.com & 1Password, among many others. Needless to say, her vista across many leading SaaS companies marketing practices is exceptional.
During the Office Hours, we’ll discuss:
the role of marketing in PLG motions.
debate the two different ways of trimming marketing spend : better to cut people or programs?
how to develop excellent positioning for a business. When to rebrand a company?
If you’re interested to attend, please register here. As always, we will collect questions from participants before the event, weave them into the conversation, and answer live questions at the end of the session.
I look forward to welcoming Carilu to Office Hours! -
Office Hours welcomed Bill Binch, former CRO at Pendo, EVP Worldwide Sales at Marketo & operating partner at Battery to share his views on building world-class sales organizations.
Bill & I exchanged emails about Deliberately Underselling as Sales Strategy. I asked him to share his views on land & expand team structure & quotas. But we covered much more. Here are three highlights from the session.
First, Deliberately Underselling means optimizing the sales process for Net Dollar Retention (NDR). Logo-based quotas focus the team on speed to close. Sometimes, these plans have a minimum contract value plus a bounty.
Another structure establishes land account executives & expand account executives. The company’s leadership should calculate sales efficiency on the combined OTE (on-target earnings) to quota ratio of these teams.
A land AE with a $300k OTE might have a $600k quota. Her land AE counterpart might also have a $300k OTE with a $2.8m quota. If they attain plan, the combined OTE/quota ratio is 0.176. Most startups operate between 0.15-0.25.
This land & expand team construct recognizes the difference in difficulty between landing & expanding accounts; also, the potential difference in ideal AE for each role. Last, the plan compensates those responsible for growing accounts with a quota - in line with Frank Slootman’s philosophy.
Second, Bill offered a bold prediction. Top startups will record 200-300% NDR as PLG becomes a dominant go-to-market strategy. Today, best-in-class tops out at 170% or so. We agree there!
Third, Bill revealed his Mojo Metric, his north-star metric. The Mojo Metric reports the net change in pipeline daily. Here’s how to calculate yours:
Mojo = new pipeline + new_pipeline_expanded + deals_pulled_forward deals_killed - deals_shrunk - deals_pushed
Each day’s Mojo reveals how much incremental pipeline the team has generated & informs the sales leader early on about this quarter’s health.
There’s much more in the session including handling commissions on multi-year deals (TCV vs ACV), criteria for evaluating ramping account executives that echoes insights from the Vista sales playbook, optimal ratios for team construction, how sales has changed in 30 years & how it changes after Covid, amongst other topics.
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Office Hours welcomed Lars Nilsson, VP Sales Development from Snowflake to talk about his learnings across 5 companies he helped take public.
Throughout the hour, Lars provided insightful perspectives on how to build sales organizations. These the five most memorable takeaways for me.
In early-stage companies, founders sell for the first three to four quarters. Then, many founders opt to hire an AE. Hiring a sales or business-development representative (SDR/BDR) can be the better choice. Incoming account executives will want to see a significant lead volume before joining, especially when selling into the enterprise.
Teams often overlook storytelling as a critical part of effective lead generation. Fear-of-missing-out or the inspiration of a potential future, stories equip champions inside customer organizations to sell the product through the buying process. Founders validate the effectiveness of their stories when hiring SDRs better. SDRs call ten-times as many prospects as AEs do. Much the better to iterate with greater speed and confidence.
As the company grows, building the sales development team becomes the most productive source of pipeline particularly for enterprise-grade technical products. Hire for hunger. Then surround the new SDR/BDR with three pillars: strong training materials, a manager who cares about the employee’s success, and a peer to accelerate learning.
At Snowflake, sales development lives within the marketing team. Lars manages his team through a single metric, meetings. Getting to an account late, a few days or a week after they’ve signed with a competitor accrues to the meeting metric (see why in the video).
Last, exiting unlikely sales processes saves the company’s resources and boosts team morale. Closed - no decision is the worst outcome of an engagement.
We covered much more in the session including the techniques Snowflake uses to align account-based marketing with sales development & sales teams; how to structure career paths within the team; transitioning accounts between SDRs/BDRs to account executives; and the right SDR:AE ratios as companies scale.
Thank you, Lars, for the masterclass on sales development.
